The Effects of Sexist Attitudes on Sexual Harassment at the Royal Military College
Bibliographic record
Abstract
Abstract The Canadian Armed Forces (CAF) has frequented the news headline as more and more stories come to light about issues of sexual harassment and misconduct within the Canadian military. The CAF has attempted to change these attitudes through the implementation of training and Operation Honour. However, despite these efforts, sexist attitudes continue to exist within this military context (Scopio, et al 2020). These attitudes are apparent at the Royal Military College of Canada (RMC) where future officers of the CAF attend university (Statistics Canada, 2020). Incidents relating to sexual harassment and sexual assault occur and are an established problem for the College (Statistics Canada, 2020). Previous research demonstrated a relationship between feminist identity and rape myth acceptance (RMA), between feminist identity and sexual harassment, and between RMA and sexual harassment (Begany & Milburn, 2002; LeMaire et al., 2016; Scopio., et al 2020). This study aimed to examine whether rape myth acceptance mediates the relationship between feminist identity and sexual harassment attitudes at the Royal Military College. Using a sample of n = 144 officer cadets at RMC, it was determined that RMA demonstrates partial indirect effects on the relationship between feminist identity and sexual harassment. References Begany, J. J., & Milburn, M. A. (2002). Psychological Predictors of Sexual Harassment: Authoritarianism, Hostile Sexism, and Rape Myths. Psychology of Men & Masculinity, 3(2), 119–126. https://doi.org/10.1037/1524-9220.3.2.119 LeMaire, K. L., Oswald, D. L., & Russell, B. L. (2016). Labeling sexual victimization experiences: The role of sexism, rape myth acceptance, and tolerance for sexual harassment. Violence and Victims, 31(2), 332–346. https://doi.org/10.1891/0886-6708.vv-d-13-00148 Maxwell, A. (2020, October 8). Experiences of unwanted sexualized and discriminatory behaviours and sexual assault among students at Canadian military colleges, 2019. Government of Canada, Statistics Canada. Retrieved February 15, 2022, from https://www150.statcan.gc.ca/n1/pub/85-002-x/2020001/article/00011-eng.htm Scoppio, G., Otis, N., Yan, Y. (L., & Hogenkamp, S. (2020). Experiences of officer cadets in Canadian military colleges and CIVILIAN UNIVERSITIES: A gender perspective. Armed Forces & Society. https://doi.org/10.1177/0095327x20905121
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".